Lead Machine Learning Analyst - Generative AI

This role sits at the intersection of generative AI engineering and enterprise product development. You will serve as a GenAI subject matter expert and hands-on architect, building production-ready solutions that combine LLMs, vector databases, and API integrations with a focus on privacy, security, and business outcomes.

Responsibilities:

• Build scalable software solutions using LLMs and other ML models to solve complex enterprise challenges.
• Architect and develop enterprise-grade AI solutions with a focus on privacy, security, fairness, and responsible AI practices.
• Design AI output structures (JSON, HTML, nested nodes) that can be consumed directly by downstream dashboards with minimal development overhead.
• Build extensible API integrations and low-code UI/UX solutions to extract, process, and surface AI insights in high-performing dashboards.
• Work with Product Development as a GenAI subject matter expert, envision solution outcomes, and design viable architectures to meet them.
• Understand how AI models interpret datasets and build prompts that reliably produce expected outcomes.
• Architect and develop infrastructure for scalable, distributed ML systems.
• Work with frameworks including TensorFlow, PyTorch, Hugging Face, LangChain, and LlamaIndex.
• Optimise generative AI models for performance, scalability, and efficiency.
• Develop and maintain AI pipelines, data preprocessing, feature extraction, model training, evaluation, and deployment.
• Contribute to the establishment of best practices and standards for GenAI development.

Requirements:

• 6+ years overall experience; 5+ years full-stack engineering (C#, Python).
• Proficiency in designing architecture, building API integrations, configuring cloud services, and setting up authentication, monitoring, and logging.
• Production experience implementing AI systems, computer vision, NLP, and/or enterprise AI at scale.
• Experience with vector databases (Pinecone or equivalent) for information retrieval.
• Strong understanding of NLG and GenAI, transformers, LLMs, and text embeddings.
• Experience designing scalable classification, text extraction, and data connector systems across formats (PDF, CSV, DOCX).
• ML libraries and frameworks: PyTorch, TensorFlow, Hugging Face, LangChain, and LlamaIndex.
• 3+ years in a technical leadership role setting technical direction for project teams.
• Programming proficiency in C/C++, Java, and Python.
• Excellent problem-solving and communication skills for both technical and non-technical audiences.
• What Will Give You an Edge: Experience with cloud-based platforms, AWS, GCP, or Azure. Exposure to self-supervised learning, transfer learning, and reinforcement learning.